Title: Ambiguous Joint Chance Constraints under Mean and Dispersion Information
Speaker: Prof. Daniel Kuhn
Affiliation: Risk Analytics and Optimization – Ecole Polytechnique Federale De Lausanne (EPFL)
Location: Room 217 Huxley Building
Time: 4:00pm

Abstract. We study joint chance constraints where the distribution of the uncertain parameters is only known to belong to an ambiguity set characterized by the mean and support of the uncertainties and by an upper bound on their dispersion. This setting gives rise to pessimistic (optimistic) ambiguous chance constraints, which require the corresponding classical chance constraints to be satisfied for every (for at least one) distribution in the ambiguity set. We provide tight conditions under which pessimistic and optimistic joint chance constraints are computationally tractable, and we show numerical results that illustrate the power of our tractability results. This is joint work with Grani Hanasusanto, Vladimir Roitch and Wolfram Wiesemann.

About the speaker. Daniel Kuhn holds the Chair of Risk Analytics and Optimization at EPFL. Before joining EPFL, he was a faculty member at Imperial College London (2007–2013) and a postdoctoral researcher at Stanford University (2005–2006). He received a Ph.D. in Economics from the University of St. Gallen in 2004 and an M.Sc. in Theoretical Physics from ETH Zürich in 1999. His research interests revolve around robust optimization and stochastic programming.